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Researcher · Nvidia (United States) · United States

Maying Shen

Maying Shen publishes mostly in Computer Vision and Pattern Recognition, Artificial Intelligence and Electrical and Electronic Engineering, on topics such as Advanced Neural Network Applications, Adversarial Robustness in Machine Learning and Domain Adaptation and Few-Shot Learning.

ORCID 0009-0000-9416-680X OpenAlex
World rank
#3,818,259
of 7,710,434 ranked researchers
Rank in United States
#1,050,976
of 1,627,098
Works
43
Citations
194
Citations per work
4.5
h-index
5
i10-index 5Top 87% in Computer Vision and Pattern Recognition
Maying Shen

What does Maying Shen research?

Maying Shen's work is mostly in Computer Science (72%), Engineering (8%), Neuroscience (3%).

Physical Sciences: 34 works · 80.2% of their workComputer Science: 31 works · 72.5% of their workComputer Vision and Pattern Recognition: 16 works · 37.1% of their workArtificial Intelligence: 14 works · 32.8% of their workComputer Networks and Communications: 1 works · 2.6% of their workEngineering: 3 works · 7.7% of their workElectrical and Electronic Engineering: 2 works · 4.3% of their workAutomotive Engineering: 1 works · 3.4% of their workEverything else: 7 works · 17.2% of their workLife Sciences: 1 works · 2.6% of their workNeuroscience: 1 works · 2.6% of their workCognitive Neuroscience: 1 works · 2.6% of their workTHEIR WORKMaying Shen43works
Life Sciences3%Physical Sciences80%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Computer Science3172.5%
    2. Engineering37.7%
  2. Everything else717.2%
    1. Neuroscience12.6%
  1. 1Computer Vision and Pattern Recognition37% of their works
  2. 2Artificial Intelligence33% of their works
  3. 3Electrical and Electronic Engineering4% of their works
  4. 4Automotive Engineering3% of their works
  5. 5Cognitive Neuroscience3% of their works
  6. 6Computer Networks and Communications3% of their works

Research topics

Which keywords describe Maying Shen's research?

The keywords of their largest research topics: Deep Learning, Convolutional Neural Networks, Neural Networks, Machine Learning, Image Recognition, Object Detection, Adversarial Examples and Robustness.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.

All 20 words, with their numbers
  1. Deep Learning497 topics
  2. Convolutional Neural Networks212 topics
  3. Neural Networks213 topics
  4. Machine Learning172 topics
  5. Image Recognition161 topic
  6. Object Detection161 topic
  7. Adversarial Examples131 topic
  8. Robustness131 topic
  9. Domain Adaptation101 topic
  10. Transfer Learning101 topic
  11. Object Tracking51 topic
  12. Visual Tracking51 topic
  13. Autonomous Vehicles41 topic
  14. Image Captioning41 topic
  15. Saliency Detection41 topic
  16. Trajectory Prediction41 topic
  17. Visual Attention41 topic
  18. Visual Question Answering41 topic
  19. Feature Matching31 topic
  20. Local Descriptors31 topic

Where does Maying Shen work?

Maying Shen's main affiliation in the publication record is Nvidia (United States), United States.

How many publications and citations does Maying Shen have?

OpenAlex counts 43 works and 194 citations for Maying Shen, an h-index of 5, ranking #3,818,259 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

Discussion

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